MSYS 181 Midterms

Information System

A set of interrelated technologies (hardware, software, network, data, processes and people) working together to collect, manipulate, store, and disseminate data and information, and provide a feedback mechanism to meet an object.

Information and Communication Technology

Refers to the use, development, and management of computer-based systems and software to store, process, transmit, and retrieve data

• Includes the use of communication technologies to enable the exchange of information

ICT as Infrastructure Stack

1. Data → To derive information

2. Network → Connection

3. Software → Interface

4. Hardware → Foundation, Physical

Hardware: Input Devices

Allows user to enter data and instructions into the computer system

• Physical interactions between user and computer system

Hardware: Output Devices

Display or present the results of processing to the user

Hardware: Processing Devices

Perform calculations and execute instructions

Hardware: Storage Devices

Store data and instrcutions for later use

Hardware: Network Devices

Enable communication and data transfer between computers and other devices

Software: System/Operating Software

Manages and controls the hardware and provides a platform for application software to run

Software: Application Software

Designed to perform specific tasks for the user

Network: Topology

Physical or logical arrangement of devices in a network (eg. server rooms, telecommunication closets, mesh)

Network: Hardware

Devices u

Network: Types

LAN

WAN

WLAN

VPN

Network: Protocols

Rules and standards that govern communication between devices on a network (eg. TCP/IP, HTTP, FTP)

Network: Software

Software used to manage and monitor network performance and security

Data: Collection

Gathering data from various sources

Data: Processing

Transforming data from unauthorized access, use, disclosure, disruption, modification, or destruction

Data: Database Management System

Software systems used to create, manage, and access database

Data: Storage

Storing data in databases, files or other storage media

Data: Analysis

Examining data to identify patterns, trends, and insights

Data: Types

Different categories of data such as numerical, textual, data, boolean, etc

Enterprise Resource Planning (ERP)

System that manages and brings together an entire organization’s operation

• Encompasses primary and secondary functions (Based on Porter’s Value Chain)

A system that optimizes the flow of information, materials, and cash in an organization

ERP Flows

Information → Inflow (Customer to Business)

Materials → Outflow (Business to Customer)

Cash → Inflow (Customer to Business)

Customer Relationship Management (CRM)

Manages a company’s customers, marketing, and sales activities

Supply Chain Management (SCM)

Handles the interconnection between the different stages of product development and delivery

Supplier Relationship Management (SRM)

Manages a company’s suppliers, negotiations, and supplier contracts

Human Capital Management (HCM)

Manages a company’s employee data and HR operations

Digital Technology

Any technology that digitizes something or processes digital data

• Encompasses Information Technology, parts of Operational Technology, and Communication Technology

Information Technology (IT)

Application of digital technology to store, retrieve, transit, and manipulate data

• Consists of hardware, system software, data, and applications

Objective of Information Technology

Make information available to its end users

Operational Technology (OT)

For detecting or causing changes in physical devices through monitoring and/ control

Objective of Operational Technology

Use digitized data to act

Internet of Things (IoT)

IT and CT connect OT devices to each other and to other information systems.

• Combination of several technologies including machine learning (IT), sensors (OT), embedded system (IT&OT), and real-time analytics (IT)

• Applies to different industries

Communication Technology (CT)

Any technology that encodes, transmits, and decodes signals, voice, or data

[QUESTION]

What does CT do for IT and OT?

Seen as a component of IT or OT.

Enables IT and OT to be highly mobile and accessible to organizations, consumers, and other stakeholders.

Digital Organization

An organization that is enabled by digital technology to:

• do business significantly different

• do a significantly different business

[QUESTION]

What does “do business significantly different” mean?

Improvements and innovation from processes of competition

[QUESTION]

What does “do a significantly different business” mean?

Create a new market

Digital Business

The activities which enable an organization to fulfill its purpose, and which are based on the use of digital technology

Digitization

Process of transforming something from analogue to digital form by expressing the information in binary digits

Digital Transformation (PeopleCert)

Use of digital technology to enable a significant improvement in the realization of the organization’s objectives that could not feasibly have been achieved by non-digital means

• Achieved through automation (digitizing, robotizing, etc)

Digital Transformation (Harvard Business Planning)

Strategically plan organizational change to promote a culture of innovation while empowering teams to create highly responsive strategies

Themes of digital transformation

1. Technology

2. Strategy/Business Model Innovation

3. Operation/Process

4. Customer

5. Value

6. Organizational Changes

7. Improvement

8. Innovation

9. New Revenue

10. Leadership

11. Sustained competitive advantage

Digital Transformation & IT transformation

IT Transformation → How Information systems & IT services are developed, run, and supported

Digital Transformation → Encompasses both IT and Business aspect of organization

Generative Artificial Intelligence (AI)

Involves the use of deep learning algorithms that can recognize, summarize, translate, predict, and generate content

Referred to as Large Language Models (LLMs)

Fourth Industrial Revolution, Industry 4.0 (4IR)

Merge physical, digital, and biological worlds that fundamentally changed the way we live, work, and relate to one another

• Focuses on speed, breadth, and depth of the development

• Opportunity to create an inclusive, human centered future

[QUESTION]

Why are the speed, breadth, and depth forcing us to rethink how development happens?

Because of how fast, how extensive, and how complex technology has been developed. 

Poses threat to the meaning of being a human.

Industry 4.0 No man’s Land

Boundary between OT and IT that cannot be crossed by the other

Industry 1.0 History

Machination thru steam power

Industry 2.0 History

Rise of electricity, mass production, assembly lines

Industry 3.0 History

Introduction of electronics, information and communications technology, automation and lead production

Industry 4.0 History

Widespread use and accessibility to electric and renewable energy, software platforms, IoT, Artificial Intelligence, Big Data Analytics, and Smart Production

Industry 5.0

Aims to foster collaboration and cohabitation between machine & human

• For sustainable and continuous innovation

Society 5.0

Human-centered society, balancing economic placement with social problem-solving

• Focuses on societal benefits and improving quality of life through technology

Four Pillars of Digital Transformation

1. Customer and Employee Experience

2. Operational Excellence

3. Business Model

4. Values & Behaviors

5. Culture

Artificial Intelligence for IT Operations (AIOps)

Uses AI and machine learning to automate and enhance IT operations, improving efficiency and reducing downtime

Machine Learning for IT operations (MLOps)

A software system to test and validate data, schemas, and models

• Automatically deploys another service (model prediction service)

Business Intelligence (IBM)

Set of technological processes for collecting, managing, and analyzing organizational data to yield insights that inform business strategies and operations

Business Intelligence (CIO)

Set of strategies and technologies for analyzing business information and transforming into actionable insights that inform strategic and tactical business decisions

Business Intelligence (Oracle)

Capabilities that enable organizations to make better decisions, take informed actions, and implement more-efficient business processes

Business Intelligence (Coursera)

Collecting, analyzing and interpreting data to gain insights and make informed decisions within an organization

Analytics Capabilities: Descriptive

What has already happened?

• Visualizes historical data

  • Most human intervention

  • Least value, least difficult

Analytics Capabilities: Diagnostic

Why did it happen?

• Understand why an occurrence happened

Analytics Capabilities: Predicitive

What will happen?

• Looking forward to trends on what can possibly happen

Analytics Capabilities: Prescriptive

What should I do?

• Based on business rules, recommend possible decisions

  • Least human intervention

  • Most value, most difficult

CRoss Industry Standard Process for Data Mining (CRISP-DM)

Provides a framework to structure thinking about data analytics problems

CRISP-DM: Business Understanding

What does the business need?

• Understand what does the business want to do

• Assess the situation of the business = capabilities, resources, requirements, risks and contingencies

  • Implement Cost-benefit analysis

CRISP-DM: Data Understanding

What data do we have/need? Is it need/accurate?

• Collect initial data

• Describe Data, document current situation of data

• Explore Data → Exploratory data analysis

• Verify data quality

CRISP-DM: Data Preparation

 How do we organize the data for modeling?

• GARBAGE IN, GARBAGE OUT: What type of data should the organization keep or delete

• Clean Data 

  • Longest process

• Construct data: Derive new attributes that will be helpful

  • What data sets should be added into the sources

• Integrate data: Create new data sets by combining data from multiple sources

• Re-format data as necessary

CRISP-DM: Modeling

What modeling techniques should we apply?

• Define structure of the data

• Select modeling techniques

• Generate

CRISP-DM: Evaluation

Which model best meets the business objectives?

• Evaluate results, how useful is the data modelling?

CRISP-DM: Deployment

How do stakeholders access the results?

• Plan Deployment

• Plan Monitoring and Maintenance

• Produce final report/summary

• Review project

Data Sources: Applications/Systems

Performa operation processesD

Data Source: Data as a Service (DaaS)

Information provision and distribution model in which data files are made available to customers over a network

Data Source: Big Data Results

Gathered from processing and analyzing large and diverse data sets made up of different structures

Types of Data: Structured

Quantitative, highly organized into rows and columns

Types of Data: Semi-structured

Does not have a predefined data model

• Bridge between structured and unstructured

• Uses tags or metadata to identify specific data characteristics and scale data into records and preset fields

Types of Data: Unstructured

Qualitative, cannot be processed and analyzed by conventional tools (ex. images, videos, audio)